3 projects for "trace" with 2 filters applied:

  • $300 Free Credits for Your Google Cloud Projects Icon
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    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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  • 1
    Agentic Data Scientist

    Agentic Data Scientist

    An end-to-end Data Scientist

    Agentic Data Scientist is an experimental AI-driven research framework that orchestrates data science workflows through autonomous agents that can reason, plan, and execute complex analytics tasks. Unlike traditional scripted pipelines, this project lets AI agents break down high-level research goals into sub-tasks such as data acquisition, cleaning, modeling, evaluation, and reporting, with minimal human direction. Each agent is designed to independently call functions, interact with data...
    Downloads: 5 This Week
    Last Update:
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  • 2
    OpenClaw Opik Observability Plugin

    OpenClaw Opik Observability Plugin

    Official plugin for OpenClaw that exports agent traces to Opik

    OpenClaw Opik Observability Plugin is an open-source plugin designed to add observability and monitoring capabilities to OpenClaw autonomous AI agents by exporting operational traces to the Opik observability platform. The project integrates directly with OpenClaw’s plugin architecture so that developers can capture detailed runtime information about how their agents behave while executing tasks. Each time an AI agent performs an action—such as calling a large language model, invoking a...
    Downloads: 10 This Week
    Last Update:
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  • 3
    Agent Lightning

    Agent Lightning

    The absolute trainer to light up AI agents

    Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling...
    Downloads: 0 This Week
    Last Update:
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